no code implementations • 26 Mar 2024 • Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi, Kyunggeun Lee, Jun Ma, Harris Teague
Large generative models such as large language models (LLMs) and diffusion models have revolutionized the fields of NLP and computer vision respectively.
no code implementations • 4 Sep 2023 • Nilesh Prasad Pandey, Marios Fournarakis, Chirag Patel, Markus Nagel
Post-training quantization (PTQ) is the go-to compression technique for large generative models, such as stable diffusion or large language models.
no code implementations • 10 Feb 2023 • Nilesh Prasad Pandey, Markus Nagel, Mart van Baalen, Yin Huang, Chirag Patel, Tijmen Blankevoort
We experimentally validate our proposed method on several computer vision tasks, natural language processing tasks and many different networks, and show that we can find mixed precision networks that provide a better trade-off between accuracy and efficiency than their homogeneous bit-width equivalents.
no code implementations • CVPR 2022 • Hyojin Park, Alan Yessenbayev, Tushar Singhal, Navin Kumar Adhikari, Yizhe Zhang, Shubhankar Mangesh Borse, Hong Cai, Nilesh Prasad Pandey, Fei Yin, Frank Mayer, Balaji Calidas, Fatih Porikli
Such a deployment scheme best utilizes the available processing power on the smartphone and enables real-time operation of our adaptive video segmentation algorithm.